Quantitative Research Analyst

Join our dynamic Volatility team at Trexquant as a highly skilled Quantitative Researcher. This crucial role involves collaborating closely with the Head of Volatility to expand our research group's capabilities, focusing on the development of specialized volatility tools and the exploration of trading signals and strategies within the volatility markets. The ideal candidate will possess a strong background in volatility modeling, statistical analysis, and a comprehensive understanding of market dynamics.Key Responsibilities:Develop and maintain proprietary pricing and analytics tools tailored for volatility research.Calibrate implied volatility surfaces across a range of options including single stock, index, and ETF options, while working with developers to implement models into backtesting and live trading systems.Design, implement, and enhance trading strategies aimed at predicting volatility market trends using extensive financial datasets and diverse trading signals.Analyze large datasets to uncover actionable alpha signals and devise effective volatility trading strategies.Investigate and leverage innovative academic research in quantitative finance to evaluate, enhance, and maximize the profitability of trading strategies.Continuously refine existing models by incorporating new data sources and advanced methodologies to improve performance and scalability.Collaborate with a team of seasoned quantitative researchers to conduct experiments, backtest hypotheses, and fine-tune strategies through comprehensive simulations and data analysis.

Role overview Squarepoint Capital is hiring a Quantitative Researcher to focus on medium-frequency volatility strategies. The position involves analyzing and developing trading approaches that target volatility across multiple asset classes. Working alongside experienced professionals, this researcher will help shape and advance the firm's trading capabilities. What you will do Analyze market data to spot and assess volatility patterns at medium frequencies Develop and refine trading strategies for various asset classes Collaborate with researchers and technologists to test and implement new ideas Drive improvements in the team’s trading performance through research and innovation Requirements Strong quantitative and analytical skills Comfort working in settings where priorities may shift quickly Interest in quantitative finance, with a focus on volatility and trading strategy development Desire to contribute within a collaborative team Location This position is based in New York.

Join our dynamic Futures team as a Quantitative Researcher and leverage your skills in financial modeling and statistical analysis to develop innovative trading models. In this pivotal role, you will engage in research and model development focused on trading and risk management in the futures markets. We are looking for a proactive candidate with a strong grasp of market dynamics and a passion for data-driven decision-making.Key Responsibilities Create, implement, and enhance trading strategies to forecast trends in the futures market using comprehensive financial data and diverse trading signals. Analyze extensive datasets to uncover actionable alpha signals and formulate effective futures trading strategies. Research and apply leading academic insights in quantitative finance to evaluate and optimize the profitability of trading strategies. Drive continuous innovation by integrating new data sources and advanced methodologies to enhance model performance and scalability. Collaborate with a team of skilled quantitative researchers to conduct experiments, backtest theories, and refine strategies through thorough simulations and analytical rigor. Qualifications BS, MS, or PhD in a STEM discipline. A minimum of 2 years of experience in quantitative research, particularly in futures markets. A strong enthusiasm for machine learning and its applications in finance. Expertise in programming languages such as Python and proficiency in statistical modeling techniques. Excellent analytical and problem-solving capabilities. Effective collaboration skills, with the ability to work independently as well as in a team setting.

About the PositionJane Street is seeking talented Quantitative Researchers to assist in developing models, strategies, and systems for pricing and trading financial instruments. You will collaborate closely with seasoned researchers dedicated to mentoring our newest team members, immersing yourself in experimental design, dataset generation, time series analysis, feature engineering, and model construction for financial datasets.At Jane Street, our researchers, engineers, and traders work in close proximity, fostering a collaborative environment to train models, design systems, and execute trading strategies. We leverage petabytes of data and operate on a computing cluster with hundreds of thousands of cores, alongside a rapidly expanding GPU cluster featuring tens of thousands of high-performance GPUs. Your daily tasks may include delving into market data, fine-tuning hyperparameters, debugging distributed training performance, or analyzing our model's trading behavior in production settings.We reject the notion of a “one-size-fits-all” modeling approach; instead, we embrace a wide array of statistical and machine learning techniques, from linear models to deep learning, adapting our methods to meet the specific needs of each problem. The most successful researchers thrive on their curiosity about how their contributions integrate into the broader framework of our trading operations, transforming their findings into actionable strategies.About YouIf you’ve never considered a career in finance, you’re not alone—many of our team members were in the same boat before joining us. If you possess a curious mind and a passion for tackling intriguing challenges, you will likely feel at home here. Ideal candidates will:Utilize logical and mathematical reasoning to approach diverse problemsExhibit intellectual curiosity; eager to ask questions, acknowledge mistakes, and pursue new knowledgeBe proficient in programming, particularly with PythonCommunicate precisely and think openly, enjoying collaboration with colleagues across various fields and expertiseWhile most candidates have a background in data science or machine learning, we prioritize your thought process and learning capability over specific knowledge. A PhD or relevant research experience is advantageous.For more insights, feel free to explore our interview process and meet some of the team.

Our MissionAt comity, we are dedicated to revolutionizing energy systems by enhancing their reliability, transparency, and efficiency. Our goal is to pave the way for a future characterized by sustainable and abundant energy. To achieve this, we employ cutting-edge statistical learning and convex optimization techniques (AI) to construct the financial frameworks essential for tomorrow's energy systems.We envision a world where energy systems are efficient, autonomous, resilient, and powered entirely by renewable energy sources. About UsFounded by industry veterans from Apple, Bluevine, Affirm, Square, and Google, our leadership team comprises Stanford alumni who possess deep expertise in complex systems, machine learning, and structured finance. Supported by esteemed investors like Maverick Ventures and Caffeinated Capital, we are aligned with our strategic objectives and vision for the platform.Your RoleWe are seeking a Quantitative Researcher for Monetization to assist in designing, deploying, and operating autonomous, systematic strategies that extract economic value from our future information (forecasts) and energy systems models, while navigating real-world market constraints. In this role, you will:Identify and prioritize market opportunities based on potential value and complexity.Architect end-to-end autonomous strategies encompassing models, forecasts, and market actions.Enhance strategy performance by utilizing metadata to inform bidding decisions.Manage the full process from information development to production-ready code, stepping in when additional resources are needed.What We Value in YouYou have applied stochastic optimization to challenges within financial or electrical engineering, operations research, or economics.You possess a strong conceptual understanding of probability theory and an aptitude for shaping and managing distributions.You bring over 5 years of design, research, and development experience within the industry.You have a profound understanding of the dynamics and structure of energy, commodity, or financial markets.You are proficient in developing and monitoring machine learning models.You are a skilled programmer, particularly in Python.Most importantly, you are driven and passionate about making a significant impact in the energy sector.

Forge Global is expanding its Research & Data Analytics team in New York. The company builds technology and data solutions for private markets, supporting innovation across industries from space exploration to artificial intelligence. Forge’s marketplace and liquidity tools help employees, employers, and investors access and manage private company shares. Role overview The Quantitative Researcher will play a key part in producing original research and strengthening Forge’s analytics capabilities. This position involves working with proprietary private market data, analyzing macroeconomic trends, and identifying emerging themes that matter to clients and stakeholders. The research produced will support clients, prospective clients, internal teams, and public audiences. What you will do Generate original research using exclusive private market data Analyze macro trends and new themes relevant to private markets Create insights and content for clients, internal partners, and public audiences Contribute to the ongoing development of Forge’s Research & Analytics functions What Forge values Boldness in pursuing new ideas and solutions Accountability in delivering accurate, impactful research Humility in collaborating with colleagues and clients

About BasisBasis is a pioneering nonprofit organization dedicated to applied AI research, driven by dual objectives that enhance each other.Our primary focus is to understand and construct intelligence. This encompasses establishing the fundamental mathematical principles of reasoning, learning, decision-making, comprehension, and explanation, alongside developing software that embodies these principles.Secondly, we aim to empower society to tackle complex challenges. This involves broadening the scale, complexity, and scope of problems we can currently address and, crucially, accelerating our future problem-solving capabilities.To realize these ambitions, we are establishing an innovative technological framework inspired by human reasoning and fostering a collaborative environment that prioritizes human values.About the RoleAs a Research Engineer, you will play a vital role in advancing Basis’ mission by converting research concepts into accurate, robust, and scalable high-quality code.We are looking for technically proficient individuals who are enthusiastic about delving deep into foundational concepts. Our research engineers are committed to conducting rigorous, high-quality science, unafraid to experiment, learn from mistakes, and explore innovative ideas.Basis thrives on collaboration, both within our team and with external partners. We seek individuals who enjoy tackling challenges greater than they can manage alone.Machine Learning Research Engineer Focus AreasThis position is aimed at experts in machine learning engineering. Key areas of focus include:Probabilistic programming and statistical inferenceDeep learningCausal inferenceProgram synthesis and analysisML Ops and systems engineeringThese areas will be explored in the context of developing reasoning systems. Research engineers will also engage with topics including programming language design and implementation, automatic differentiation, and SAT/SMT solvers.

About BasisBasis is a nonprofit organization dedicated to applied AI research, striving to achieve two interconnected objectives.Firstly, we aim to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; along with creating software that embodies these principles.Secondly, we seek to enhance society's capacity to address complex challenges. This means broadening the range, scale, and intricacies of the problems we can tackle today, while also accelerating our ability to solve future challenges.To fulfill these missions, we are constructing a novel technological framework inspired by human reasoning, and fostering a collaborative organization that prioritizes human values.About the RoleAs a Research Scientist, you will spearhead Basis's initiatives to deepen our comprehension of the theoretical, mathematical, and computational aspects of intelligence.We seek individuals with exceptional technical skills who are passionate about exploring concepts at their core. Our research scientists and engineers are committed to conducting rigorous, high-quality, and robust scientific inquiry, yet they embrace experimentation, learning from mistakes, and exploring innovative ideas to achieve their goals.Basis thrives on collaboration, both internally and with external partners; thus, we value team players who relish tackling challenges that surpass individual capabilities.Research FocusOur research under the MARA project is dedicated to forging new principles and technologies for modeling, abstraction, and reasoning in AI systems. The primary aim of MARA is to reveal principled methodologies for how intelligence constructs, refines, and applies world models through interactive experimentation.For this position, we specifically seek experts in Reinforcement Learning & Planning who can push the boundaries of model-based RL, exploration strategies, optimal control, and Bayesian optimization. You will develop agents capable of learning efficient policies in intricate, partially observable environments by utilizing structured world models.

Overview: Join Guidepoint's dynamic Market Research Team as the Director of Quantitative Panel, where you will spearhead the growth, management, and maintenance of our expert research community for quantitative surveys. This pivotal role involves crafting outreach strategies, ensuring panel quality and health, and overseeing custom recruitment operations to enhance our panelist experience. This is a hybrid role based in our New York office, with an option for full remote work. Key Responsibilities: Lead the management of Guidepoint’s quantitative survey panel community, focusing on database administration, respondent engagement, retention metrics, and customized recruitment strategies. Collaborate with both internal and external vendors to create tools and systems for feasibility assessments in research and project bidding for quantitative survey initiatives. Provide strategic direction on panelist engagement, optimizing both email outreach and alternative invitation methods to enhance community participation. Partner with IT/Engineering to ensure seamless integration between Guidepoint’s expert network and quantitative respondent databases, maintaining data accuracy and comprehensiveness. Work alongside the Advisor Relations team to develop a response strategy and playbook addressing survey-related advisor concerns, including technical issues, survey satisfaction, and incentive management. Oversee the expansion of the panel through custom recruitment efforts, managing both personnel and systems like ContactOut and AggKnowledge to meet project demands and bolster proactive sales capabilities. Ensure panelist quality through effective vetting systems, promptly addressing any quality concerns by quarantining or removing panelists who do not meet established thresholds. Perform additional duties as required. Qualifications: A minimum of 10 years of experience managing an international market research panel or a large membership organization, with a preference for backgrounds in the medical or enterprise B2B sectors. Proficiency in database and contact management utilizing a CRM or market research panel management platform (e.g., Forsta, Qualtrics, RallyUXR) or other SQL-based data management tools. Experience in email marketing, outreach techniques, A/B testing, and campaign optimization. Strong collaboration skills with technical product and engineering teams on data engineering and web development projects. A demonstrated ability to engage with diverse stakeholders and drive community growth and satisfaction.

About the Role The International Crisis Group is seeking a Quantitative Research Intern to join the eEARTH Project. This position supports analysts working on research related to resource-driven conflicts. Interns will gain practical experience in conflict analysis, earth observation, and advocacy within a respected international NGO. Location This internship can be based in New York, USA; Nairobi, Kenya; or Brussels, Belgium. Eligibility Open to students currently enrolled in an academic program who can earn academic credit for the internship Also available to candidates who have secured external funding (such as grants or scholarships) to support their participation Work Arrangement This is a desk-based internship.

Join IMC as a Quantitative Developer, where you will take charge of transforming research into actionable trading strategies. This position uniquely combines research and engineering, allowing for continuous feedback from the initial concept to live trading. Your role will involve creating sophisticated systems that leverage quantitative insights to develop a competitive edge, with direct visibility into the impact of your contributions.

About the FellowshipPostdoctoral Fellowships at Basis provide a unique opportunity for distinguished researchers to advance their expertise in the field of computational intelligence. This encompasses areas such as reasoning, learning, and decision-making. Fellows will collaborate closely with Basis Research Scientists and esteemed Principal Investigators (PIs) from leading academic institutions.About BasisBasis is a nonprofit organization dedicated to applied AI research, driven by two interdependent goals.Our primary aim is to understand and develop intelligence. This involves establishing the mathematical foundations of reasoning, learning, decision-making, comprehension, and explanation; and creating software that embodies these principles.Secondly, we strive to enhance society's capability to tackle complex problems. This entails broadening the scope and complexity of challenges we can address today and, crucially, expediting our future problem-solving abilities.To fulfill these objectives, we are constructing a new technological framework inspired by human reasoning and fostering an innovative collaborative organization that prioritizes human values.How it WorksPostdoctoral Fellows at Basis are jointly mentored and funded by Basis and partner PIs from academic institutions. Fellows will divide their time between Basis and their academic PI's lab, functioning as part of a jointly advised postdoctoral program.Our established partner PIs include: Nada Amin (Harvard), Kevin Ellis (Cornell), Armando Solar-Lezama (MIT), Youssef Marzouk (MIT), and Tom Silver (Princeton).Each Fellow is paired with a mentor from Basis, chosen to align with their research interests and aspirations.Potential Basis mentors possess a wealth of expertise in various fields, ensuring a tailored and enriching mentorship experience.

About BasisBasis is a pioneering nonprofit organization specializing in applied AI research, dedicated to achieving two synergistic objectives.The first objective is to comprehend and develop intelligence. This encompasses establishing the mathematical foundations of reasoning, learning, decision-making, understanding, and explanation; subsequently, we construct software that embodies these principles.The second objective is to enhance society's capacity to tackle complex issues. This involves broadening the scope, intricacy, and variety of challenges we can address today, while also accelerating our future problem-solving capabilities.To fulfill these ambitious goals, we are creating a robust technological foundation inspired by human reasoning, alongside a collaborative organization that prioritizes human values.About the RoleWe are in search of a Technical Program Manager who possesses a deep passion for program management and is eager to propel ambitious research initiatives. In this role, you will be the crucial link connecting our researchers, engineering teams, leadership, and external partners, requiring both technical acumen and project management skills.

Join IMC, a leading global market maker, as a Quantitative Researcher specializing in Equities. In this role, you will develop cutting-edge high-frequency, low-latency trading strategies and predictive models. Collaborate with a talented team to blend IMC's extensive options expertise with insights from the equity market. Your analyses will drive unique predictions of market behavior, which will be executed using our state-of-the-art technology across both options and equities markets.As a valued member of our growing team, you will be integral to all facets of IMC’s trading operations. Your contributions will extend beyond signal generation to collaborating with developers in designing and implementing a robust framework that fosters timely research, testing, and production of new ideas.

Join Our Team as a Quantitative ResearcherEngineers Gate (EG) is at the forefront of quantitative investment, specializing in computer-driven trading across global financial markets. Our team comprises talented researchers, engineers, and finance professionals dedicated to leveraging advanced statistical models to analyze data and uncover predictive signals that yield exceptional investment returns. Each investment team operates with distinct strategies while utilizing our proprietary technology and data platform to enhance alpha research.We are looking for a driven and experienced Quantitative Researcher to become a vital part of one of our systematic equity trading teams. In this position, you will harness the existing research and trading frameworks to create innovative systematic trading strategies throughout their lifecycle—from comprehensive data analysis to idea generation, backtesting, and eventual deployment. The ideal candidate will possess robust programming skills and a passion for in-depth data analysis, facilitating creative alpha generation based on a profound understanding of data and financial acumen. As a member of a small team, you will report directly to the Portfolio Manager, engaging in all facets of systematic trading, which presents substantial growth opportunities for the right individual.We emphasize continuous learning and professional development, making this role a unique chance to collaborate and learn from seasoned experts in the field.At Engineers Gate, we are committed to advancing systematic trading through innovative quantitative analysis. If you thrive in a dynamic, data-driven environment, we invite you to apply and join us on this exciting journey.

About BasisBasis is a pioneering nonprofit organization focused on applied AI research, driven by dual objectives.Our first goal is to comprehend and construct intelligence. We endeavor to lay down the mathematical principles defining reasoning, learning, decision-making, understanding, and explanation, while also developing software that embodies these principles.The second aim is to enhance society's capability to tackle complex challenges. We strive to broaden the scale, complexity, and diversity of problems we can address today, and more critically, to hasten our capacity to resolve future challenges.To fulfill these ambitions, we are creating an innovative technological foundation inspired by human reasoning, alongside a collaborative organization that prioritizes human values.About the RoleAs a Data Engineer on the Platform team at Basis, you will be responsible for constructing reliable data pipelines featuring comprehensive provenance and quality controls. You will curate documented datasets for training and evaluation while ensuring that our data infrastructure scales effectively. Your work will encompass both platform-specific data needs and cross-project data coordination, minimizing redundancy and fostering shared datasets.We are in search of technically proficient individuals who regard data quality as paramount. The ideal candidate has experience with machine learning data pipelines, understands the complete lifecycle from raw data to model training and evaluation, and approaches data provenance, lineage tracking, and quality assurance with rigor. You will blend software engineering best practices with a profound understanding of data systems and machine learning requirements.This role operates across both the Platform and Research teams, working on infrastructure that supports our commercial offerings and internal research initiatives. You will play a vital role in scaling Basis's data operations to support medium-scale models, ensuring data governance as we cater to external clients, and building systems that researchers can rely on for reproducible experiments.We seek individuals who are committed to executing high-quality, robust data engineering while remaining open to iteration, learning from real-world usage, and exploring diverse approaches to achieve excellence.At Basis, collaboration is key—both internally and with our external partners. We value those who enjoy laying the groundwork for solving grand challenges that extend beyond individual efforts.

Join Virtu Financial, a leading quantitative trading firm, where innovation meets impact in the financial markets. As a Machine Learning Researcher, you will engage in groundbreaking research opportunities within a dynamic and agile organization. This role presents a unique blend of intellectual challenge and immediate business influence, as you navigate complex problems that lack straightforward solutions.Your responsibilities will encompass our entire modeling ecosystem, from feature engineering and deep learning architecture to training dynamics and execution strategies. Your pioneering contributions will shape our market operations globally, making a real difference in a fast-evolving industry that thrives on creative problem-solving and first-principles thinking.We seek individuals with a strong sense of curiosity, a robust technical skill set, and a collaborative spirit, regardless of their industry background.

Position OverviewJane Street is seeking talented Quantitative Researchers to join our innovative team. In this role, you will develop advanced models, strategies, and systems for pricing and trading financial instruments. Your expertise in experimental design, dataset generation, time series analysis, feature engineering, and model building will be applied to financial datasets, all while collaborating with a team of experts who will challenge and enhance your methodologies.At Jane Street, our researchers, engineers, and traders work closely together in a dynamic environment, leveraging petabytes of data and a vast GPU cluster equipped with tens of thousands of high-performance GPUs. Your day might involve deep analysis of market data, tuning hyperparameters, debugging distributed training issues, or evaluating how our models perform in real-world trading scenarios.We value diversity in our modeling solutions, embracing a broad range of statistical and machine learning techniques, from linear models to deep learning, tailored to meet the unique challenges we face. The most successful researchers will possess a strong curiosity about how their work contributes to our trading operations and how to translate their insights into actionable strategies.

Join our dynamic team at comity as a Quantitative Researcher for Congestion Revenue Rights. In this pivotal role, you will engage in in-depth analysis and research to optimize congestion revenue rights, contributing to innovative solutions in the transportation sector. Your expertise will help shape strategies that enhance operational efficiency and profitability.